To identify lithologies, geoscientists use subsurface data such as wireline logs and petrophysical data. However, this process is often tedious, repetitive, and time-consuming. This project aims to use machine learning techniques to predict lithology from petrophysical logs, which are direct indicators of lithology.

Machine Learning model to predict the health of the car engines using various algorithms like KNN, SVM, Random Forest, Xboost Classifier.

End-to-end project to predict basketball player points. (regression problem)

how to predict score credit to home credit indonesia with machine learning modeling, find more to Home Credit Indonesia

Implemented time series forecasting to predict future orders for Glovo, utilizing models such as ARIMA/SARIMA, LASSO, XGBoost, and Linear Regression.

XGBoost vasitəsilə neftin gələcək qiymətinin proqnozlaşdırılması layihəsi

Proyecto de predicción de ventas para las proximas 6 semanas de todas las tiendas , con representación de datos, usando Python con librerías distintas como Pandas, Numpy,Matlab, Seaborn para análisis de datos, recopilación e interpretación de los datos, además de modelos predictivos.

Augmentation based on position applied to CRF and XGBOOST algorithms applied to african languages for POS task